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    <title>Database Commons - Help</title>
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        <li class="active">Help</li>
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        <h3><i class="fa fa-question-circle"></i> Help</h3>
        <hr>
        <h4>About</h4>
        <p class="text-justify">
            Database Commons is a curated catalogue of biological databases, providing people with easy access to a comprehensive collection of publicly available biological databases encompassing different data types and spanning diverse organisms. It integrates relevant information for all collected databases (including database name, URL, description, hosted institution, related publication(s), contact information, etc.) and catalogues each database based on its data type, organism and locating, accordingly enabling people to easily find a specific collection of databases of interest.
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        <p class="text-justify">
            Database Commons allows any one to rate any database by considering data quality & quantity, content organization & presentation, and system accessibility & reliability, facilitating efficient location of appropriate databases of interest.
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        <p class="text-justify">
            Together, Database Commons features cataloguing databases under different criteria and incorporating community rating on database utility, thus serving as a valuable resource for effective exploitation of all publicly available databases.
        </p>
        <p class="text-justify">
            To date, databases in Database Commons are collected primarily from journals including Nucleic Acid Research, Database, Bioinformatics, BMC Bioinformatics, etc.
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        <h4>Data Type</h4>
        <p class="text-justify">
            A database may encompass multiple data types. In Database Commons, there are a total of 14 data types as detailed below.
        </p>
        <ol>
            <li><b>Disease</b>: diseases in human, animal and plant</li>
            <li><b>DNA</b>: gene/chromosome/genome sequence, DNA mutation, DNA modification, DNA probe or primer, DNA motif and structure, repeat sequence, DNA elements</li>
            <li><b>Drug and Chemical Compound</b>: drugs, chemical compound used in experiments or existing in environment, effects of drug and chemical compound</li>
            <li><b>Expression</b>: RNA/protein expression, differential expression pattern, array/sequencing expression data
            <li><b>Interaction and Network</b>: protein-protein interaction, RNA-protein interaction, genetic interaction, metabolic interaction, gene regulatory interaction, signaling interaction, drug-target interaction, biochemical reaction</li>
            <li><b>Literature</b>: literature database, literature/text mining</li>
            <li><b>Metabolic and Signaling Pathway</b>: biological pathways for metabolic, signaling, regulatory pathway analysis</li>
            <li><b>Metadata</b>: database collection, metadata information of a project or experiment</li>
            <li><b>Modification</b>: DNA/RNA/protein modification</li>
            <li><b>Phenotype</b>: genotype-phenotype associations and their genomics relevance </li>
            <li><b>Protein</b>: protein sequence, protein family and domains, protein modification, protein-protein interaction, protein motif and structure, protein expression, antigen and antibody</li>
            <li><b>RNA</b>: mRNA transcripts, alternative splicing, ncRNA, RNA mutation, RNA modification, RNA probe or primer, RNA motif and structure, RNA expression</li>
            <li><b>Standard, Ontology and Nomenclature</b>: gene ontology, standard and nomenclature for biological entities</li>
            <li><b>Structure</b>: DNA/RNA/protein/chromatin structure</li>
        </ol>

        <hr>

        <h4>Community Rating</h4>
        <p>
            Database Commons features community rating on database utility by taking account of the following three criteria.
        </p>
        <ul>
            <li>
                <b>Data quality & quantity</b>: consider data integrity, accuracy, standardization, consistency and comprehensiveness
            </li>

            <li>
                <b>Content organization & presentation</b>: consider whether content is organized in an appropriate manner which makes content easily readable and understandable and is presented by user friendly web interface<br/>
            </li>

            <li>
                <b>System accessibility & reliability</b>: consider whether system is always accessible and reliably working<br/>
            </li>
        </ul>

        <p>
            A database containing high-quality curated data is abortive if data is poorly organized or presented.
        </p>
        <p>
            A database containing high-quality curated data is unavailing if this database cannot be accessible or reliably working.
        </p>

        <hr>

        <h4>HTTP Status Codes</h4>
        <p>
            Here is a list of HTTP status codes with a brief explanation, which are represented by three digits and fall into five classes.
        </p>

        <ul>
            <li>
                <b>1xx Informational</b>: e.g., <b>101</b> Switching Protocols
            </li>

            <li>
                <b>2xx Success</b>: e.g., <b>200</b> OK, that is standard response for successful HTTP requests.
            </li>

            <li>
                <b>3xx Redirection</b>: e.g., <b>301</b> Moved Permanently
            </li>

            <li>
                <b>4xx Client Error</b>: e.g., <b>403</b> Forbidden, <b>404</b> Not Found
            </li>

            <li>
                <b>5xx Server Error</b>: e.g., <b>500</b> Internal Server Error, <b>503</b> Service Unavailable
            </li>
        </ul>

        <p>
            More information about HTTP status code can be found at <a href="https://en.wikipedia.org/wiki/List_of_HTTP_status_codes" target="_blank">Wikipedia</a>.
        </p>

        <p>
            In addition, unexpected exceptions including timeout, errors occurred when sending requests, etc., are indicated by <b>"-1"</b>.
        </p>

        <hr>

        <h4>Contact Information</h4>

        <address>
            <strong>BIG Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences</strong><br/>
            No.1 Beichen West Road<br/>
            Chaoyang District, Beijing 100101<br/>
            China<br/>
            <br/>

            <strong>Email</strong>: Dr. Lina Ma (malina (AT) big.ac.cn), Dr. Zhang Zhang (zhangzhang (AT) big.ac.cn)<br/>
            <strong>Tel</strong>: +86 (10) 84097845<br/>
            <strong>Fax</strong>: +86 (10) 84097298<br/>
        </address>

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